Improving Quantitative Microwave Holography Through Simultaneous Use of the Born and Rytov Approximations
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Microwave near-field imaging has shown marked progress in biomedical diagnostics, including stroke detection and cancer diagnostics, though clinical devices are not yet available. The challenge of achieving high-quality image reconstruction in real time stems from the complexities of near-field scattering in the strongly heterogeneous tissue environment. Recent experiments have demonstrated the ability of quantitative microwave holography (QMH) to reconstruct the permittivity of complex tissue phantoms in real time. QMH has been applied so far in two separate versions, one based on Born’s approximation of the data equation of scattering and the other based on Rytov’s approximation. Here, we show how to reconstruct the quantitative images using both approximations simultaneously. This new reconstruction leads to images of improved resolution and quantitative accuracy compared to the two previous QMH versions. Experiments with tissue phantoms demonstrate the improvement.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it